Boosting Our Development Velocity Tenfold Using Agentic AI Coding and a Personalized “Orchestration” Framework
Revolutionizing Development Speed with AI-Powered Orchestration: Our Experience with Agentic AI and Custom Workflow Layers
In the fast-paced world of software development, efficiency and innovation are everything. Recently, we embarked on a transformative journey by integrating advanced AI agents into our development pipeline, enabling us to deliver months’ worth of features on a weekly basis. This article offers an inside look at how leveraging AI tools like Claude Code, CodeRabbit, and a proprietary “Orchestration” layer has revolutionized our processes.
The Core of Our Approach
The key to our success lies in enabling AI agents not only to generate code but to conduct mutual code reviews, fostering a collaborative environment that mimics peer review among developers. This cyclical review process significantly enhances code quality and accelerates delivery timelines.
Our Workflow in Detail
- Initiation: A task begins in our project management system.
- Task Retrieval: AI agents fetch assigned tasks through customized commands.
- Contextual Analysis: The AI reviews our entire codebase, design documents, documentation, and conducts web research if necessary.
- Task Planning: It then crafts a comprehensive task description, including specific testing criteria.
- Implementation: AI develops production-ready code aligned with our standards.
- Pull Request Creation: A GitHub pull request is automatically generated.
- Code Review: A secondary AI agent examines the proposed changes in detail, line by line.
- Feedback Loop: The first AI responds to the review, either accepting suggestions or providing justifications for its original approach.
- Learning & Adaptation: Both AI systems learn from these interactions, storing insights for future tasks.
Remarkably, this process results in approximately 98% of the code being ready for deployment before human intervention.
Observing AI Collaboration in Action
One of the most fascinating aspects is witnessing AI agents “debate” implementation strategies directly within GitHub comments. They effectively teach each other, enhancing their understanding of our codebase and refining their development capabilities without human prompting.
To see this process in action, we’ve prepared a short 10-minute walkthrough video: Watch it here.
Beyond Development: Exploring New Frontiers
While our current focus is on optimizing development workflows, we’re exploring how this AI orchestration can extend to other areas like customer support and marketing
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